diff --git a/modules/deeplearning/icing_fcn.py b/modules/deeplearning/icing_fcn.py
index 378f8725774e95c196b729ede4de710c155f15bc..ac97090cfae90085854bf42a273abf14bc36d013 100644
--- a/modules/deeplearning/icing_fcn.py
+++ b/modules/deeplearning/icing_fcn.py
@@ -130,26 +130,28 @@ def build_residual_block_1x1(input_layer, num_filters, activation, block_name, p
 
 class IcingIntensityFCN:
     
-    def __init__(self, day_night='DAY', l1b_or_l2='both', use_flight_altitude=False, gpu_device=0, datapath=None):
-
-        if day_night == 'DAY':
-            self.train_params_l1b = train_params_l1b_day
-            self.train_params_l2 = train_params_l2_day
-            if l1b_or_l2 == 'both':
-                self.train_params = train_params_l1b_day + train_params_l2_day
-            elif l1b_or_l2 == 'l1b':
-                self.train_params = train_params_l1b_day
-            elif l1b_or_l2 == 'l2':
-                self.train_params = train_params_l2_day
-        else:
-            self.train_params_l1b = train_params_l1b_night
-            self.train_params_l2 = train_params_l2_night
-            if l1b_or_l2 == 'both':
-                self.train_params = train_params_l1b_night + train_params_l2_night
-            elif l1b_or_l2 == 'l1b':
-                self.train_params = train_params_l1b_night
-            elif l1b_or_l2 == 'l2':
-                self.train_params = train_params_l2_night
+    def __init__(self, day_night='DAY', l1b_or_l2='both', satellite='GOES16', use_flight_altitude=False, datapath=None):
+
+        # if day_night == 'DAY':
+        #     self.train_params_l1b = train_params_l1b_day
+        #     self.train_params_l2 = train_params_l2_day
+        #     if l1b_or_l2 == 'both':
+        #         self.train_params = train_params_l1b_day + train_params_l2_day
+        #     elif l1b_or_l2 == 'l1b':
+        #         self.train_params = train_params_l1b_day
+        #     elif l1b_or_l2 == 'l2':
+        #         self.train_params = train_params_l2_day
+        # else:
+        #     self.train_params_l1b = train_params_l1b_night
+        #     self.train_params_l2 = train_params_l2_night
+        #     if l1b_or_l2 == 'both':
+        #         self.train_params = train_params_l1b_night + train_params_l2_night
+        #     elif l1b_or_l2 == 'l1b':
+        #         self.train_params = train_params_l1b_night
+        #     elif l1b_or_l2 == 'l2':
+        #         self.train_params = train_params_l2_night
+
+        self.train_params = get_training_parameters(day_night=day_night, l1b_andor_l2=l1b_or_l2, satellite=satellite)
 
         self.train_data = None
         self.train_label = None
@@ -189,7 +191,6 @@ class IcingIntensityFCN:
         self.accuracy = None
         self.loss = None
         self.pred_class = None
-        self.gpu_device = gpu_device
         self.variable_averages = None
 
         self.global_step = None
@@ -1097,7 +1098,7 @@ class IcingIntensityFCN:
 
 
 def run_restore_static(filename_l1b, filename_l2, ckpt_dir_s_path, day_night='DAY', l1b_or_l2='both',
-                       use_flight_altitude=False, flight_level=0):
+                       satellite='GOES16', use_flight_altitude=False, flight_level=0):
     ckpt_dir_s = os.listdir(ckpt_dir_s_path)
     cm_s = []
     prob_s = []
@@ -1107,7 +1108,7 @@ def run_restore_static(filename_l1b, filename_l2, ckpt_dir_s_path, day_night='DA
         ckpt_dir = ckpt_dir_s_path + ckpt
         if not os.path.isdir(ckpt_dir):
             continue
-        nn = IcingIntensityFCN(day_night=day_night, l1b_or_l2=l1b_or_l2, use_flight_altitude=use_flight_altitude)
+        nn = IcingIntensityFCN(day_night=day_night, l1b_or_l2=l1b_or_l2, satellite=satellite, use_flight_altitude=use_flight_altitude)
         nn.flight_level = flight_level
         nn.run_restore(filename_l1b, filename_l2, ckpt_dir)
         cm_s.append(tf.math.confusion_matrix(nn.test_labels.flatten(), nn.test_preds.flatten()))
@@ -1179,8 +1180,8 @@ def run_evaluate_static_avg(data_dct, ll, cc, ckpt_dir_s_path, day_night='DAY',
     return ice_lons, ice_lats, preds_2d
 
 
-def run_evaluate_static(data_dct, num_tiles, ckpt_dir_s_path, day_night='DAY', l1b_or_l2='both', prob_thresh=0.5,
-                        flight_levels=[0, 1, 2, 3, 4], use_flight_altitude=False):
+def run_evaluate_static(data_dct, num_tiles, ckpt_dir_s_path, day_night='DAY', l1b_or_l2='both', satellite='GOES16',
+                        prob_thresh=0.5, flight_levels=[0, 1, 2, 3, 4], use_flight_altitude=False):
 
     ckpt_dir_s = os.listdir(ckpt_dir_s_path)
     ckpt_dir = ckpt_dir_s_path + ckpt_dir_s[0]
@@ -1191,7 +1192,7 @@ def run_evaluate_static(data_dct, num_tiles, ckpt_dir_s_path, day_night='DAY', l
     probs_dct = {flvl: None for flvl in flight_levels}
     preds_dct = {flvl: None for flvl in flight_levels}
 
-    nn = IcingIntensityFCN(day_night=day_night, l1b_or_l2=l1b_or_l2, use_flight_altitude=use_flight_altitude)
+    nn = IcingIntensityFCN(day_night=day_night, l1b_or_l2=l1b_or_l2, satellite=satellite, use_flight_altitude=use_flight_altitude)
     nn.num_data_samples = num_tiles
     nn.build_model()
     nn.build_training()